1.3k citations · 3k across the 35 of their papers we have counts for
36 papers
A Kubernetes 'Bridge' operator between cloud and external resources
Boris Lublinsky, Elise Jennings, Viktória Spišaková
Many scientific workflows require dedicated compute resources, including HPC clusters with optimized software, quantum resources, and dedicated hardware cluster systems like Ray, f…
Deploying deep learning in OpenFOAM with TensorFlow
Romit Maulik, Himanshu Sharma, Saumil Patel +2
We outline the development of a data science module within OpenFOAM which allows for the in-situ deployment of trained deep learning architectures for general-purpose predictive ta…
Bayesian Neural Networks at Scale: A Performance Analysis and Pruning Study
Himanshu Sharma, Elise Jennings
Bayesian neural Networks (BNNs) are a promising method of obtaining statistical uncertainties for neural network predictions but with a higher computational overhead which can limi…
Enabling real-time multi-messenger astrophysics discoveries with deep learning
E. A. Huerta, Gabrielle Allen, Igor Andreoni +57
Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data, which vary in volume and speed of data processing, from many different instruments that…
A turbulent eddy-viscosity surrogate modeling framework for Reynolds-Averaged Navier-Stokes simulations
Romit Maulik, Himanshu Sharma, Saumil Patel +2
The Reynolds-averaged Navier-Stokes (RANS) equations for steady-state assessment of incompressible turbulent flows remain the workhorse for practical computational fluid dynamics (…
Scaling Distributed Training of Flood-Filling Networks on HPC Infrastructure for Brain Mapping
Wushi Dong, Murat Keceli, Rafael Vescovi +9
Mapping all the neurons in the brain requires automatic reconstruction of entire cells from volume electron microscopy data. The flood-filling network (FFN) architecture has demons…